Close menu


Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

Modelling the wasted value of data in maintenance investments

Marttonen-Arola, Salla, Baglee, David, Yla-Kujala, Antti, Sinkkonen, Tiina and Kärri, Timo (2020) Modelling the wasted value of data in maintenance investments. Journal of Quality in Maintenance Engineering. ISSN 1355-2511

Item Type: Article


Purpose – Big data and related technologies are expected to drastically change the way industrial
maintenance in managed. However, at the moment many companies are collecting large amounts of data
without knowing how to systematically exploit it. It is therefore important to find new ways of evaluating
and quantifying the value of data. This paper addresses the value of data –based profitability of
maintenance investments.
Design/methodology/approach – An analytical Wasted Value of Data –model is presented to quantify
how the value of data can be increased through eliminating waste. The use of the model is demonstrated
with a case example of a maintenance investment appraisal of an automotive parts manufacturer.
Findings – The presented model contributes to the gap between the academic research and the solutions
implemented in practice in the area of value optimization. The big data hype has led organizations into
gathering data without systematic exploitation plans, but it is crucial to evaluate if the benefits of the
investment will exceed the additional costs.
Originality/value – The model is designed and developed on the principle of eliminating waste to
increase value, which has not been previously extensively discussed in the context of data management.

Modelling the wasted value of data in maintenance investments.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.

Download (334kB) | Preview

More Information

Depositing User: Leah Maughan


Item ID: 12676
Identification Number:
ISSN: 1355-2511
Official URL:

Users with ORCIDS

ORCID for David Baglee: ORCID iD

Catalogue record

Date Deposited: 09 Oct 2020 10:01
Last Modified: 11 Jan 2021 16:51


Author: David Baglee ORCID iD
Author: Salla Marttonen-Arola
Author: Antti Yla-Kujala
Author: Tiina Sinkkonen
Author: Timo Kärri

University Divisions

Faculty of Technology > School of Engineering

Actions (login required)

View Item View Item